Distribution of emm types among group A Streptococcus isolates from children in Korea

Global Streptococcus pyogenes strain diversity, disease associations, and implications for vaccine development: a systematic review

The high strain diversity of Streptococcus pyogenes serves as a major obstacle to vaccine development against this leading global pathogen. We did a systematic review of studies in PubMed, MEDLINE, and Embase that reported the global distribution of S pyogenes emm-types and emm-clusters from Jan 1, 1990, to Feb 23, 2023. 212 datasets were included from 55 countries, encompassing 74 468 bacterial isolates belonging to 211 emm-types. Globally, an inverse correlation was observed between strain diversity and the UNDP Human Development Index (HDI; r=-0·72; p<0·0001), which remained consistent upon subanalysis by global region and site of infection. Greater strain diversity was associated with a lower HDI, suggesting the role of social determinants in diseases caused by S pyogenes. We used a population-weighted analysis to adjust for the disproportionate number of epidemiological studies from high-income countries and identified 15 key representative isolates as vaccine targets. Strong strain type associations were observed between the site of infection (invasive, skin, and throat) and several streptococcal lineages. In conclusion, the development of a truly global vaccine to reduce the immense burden of diseases caused by S pyogenes should consider the multidimensional diversity of the pathogen, including its social and environmental context, and not merely its geographical distribution.

Distribution of emm genotypes in group A streptococcus isolates of Korean children from 2012 to 2019

OBJECTIVES

Changes in the epidemiology of group A streptococcus (GAS) infection is related to emm genotype. We studied the distribution of emm genotypes and their antibiotic susceptibility among Korean children.

METHODS

Isolates from children with GAS infection between 2012 and 2019 were collected. emm typing and cluster analysis was performed according to the Centers for Disease Control emm cluster classification. Antimicrobial susceptibility was tested using the E-test and resistance genes were analyzed for macrolide resistant phenotypes.

RESULTS

Among 169 GAS isolates, 115 were from children with scarlet fever. Among invasive isolates, emm1 (6/22, 27.3%), emm12 (4/22, 18.2%), and emm4 (4/22, 18.2%) were most common. In scarlet fever, although emm4 (38/115, 33.0%) was the most prevalent throughout the study period, emm4 was replaced by emm3 (28/90, 31.1%) during an outbreak in 2017-2018. Among all isolates, only 2 (1.2%) exhibited erythromycin resistance and harbored both ermA and ermB genes.

CONCLUSIONS

In this analysis of GAS isolated from Korean children, emm1 was the most prevalent in invasive infection. In scarlet fever, emm4 was prevalent throughout the study period, with an increase in emm3 during 2017-2018. GAS isolates during 2012-2019 demonstrated low erythromycin resistance.

A global snapshot on the prevalent macrolide-resistant emm types of Group A Streptococcus worldwide, their phenotypes and their resistance marker genotypes during the last two decades: A systematic review

Watchful epidemiological surveillance of macrolide-resistant Group A Streptococcus (MRGAS) clones is important owing to the evolutionary and epidemiological dynamic of GAS. Meanwhile, data on the global distribution of MRGAS emm types according to macrolide resistance phenotypes and genotypes are scant and need to be updated. For this, the present systematic review analyses a global set of extensively characterized MRGAS isolates from patients of diverse ages and clinical presentations over approximately two decades (2000 to 2020) and recaps the peculiar epidemiological features of the dominant MRGAS clones. Based on the inclusion and exclusion criteria, 53 articles (3593 macrolide-resistant and 15,951 susceptible isolates) distributed over 23 countries were dissected with a predominance of high-income countries over low-income ones. Although macrolide resistance in GAS is highly variable in different countries, its within-GAS distribution seems not to be random. emm pattern E, 13 major emm types (emm12, 4, 28, 77, 75, 11, 22, 92, 58, 60, 94, 63, 114) and 4 emm clusters (A-C4, E1, E6, and E2) were significantly associated with macrolide resistance. emm patterns A-C and D, 14 major emm types (emm89, 3, 6, 2, 44, 82, 87, 118, 5, 49, 81, 59, 227, 78) and 3 well-defined emm clusters (A-C5, E3, and D4) were significantly associated with macrolide susceptibility. Scrutinizing the tendency of each MRGAS emm type to be significantly associated with specific macrolide resistance phenotype or genotype, interesting vignettes are also unveiled. The 30-valent vaccine covers ~95% of MRGAS isolates. The presented data urge the importance of comprehensive nationwide sustained surveillance of MRGAS circulating clones particularly in Low and Middle income countries where sampling bias is high and GAS epidemiology is obfuscated and needs to be demystified.

Spatiotemporal clustering and meteorological factors affected scarlet fever incidence in mainland China from 2004 to 2017

OBJECTIVE

To analyze the spatiotemporal dynamic distribution and detect the related meteorological factors of scarlet fever from an ecological perspective, which could provide scientific information for effective prevention and control of this disease.

METHODS

The data on scarlet fever cases in mainland China were downloaded from the Data Center of the China Public Health Science, while monthly meteorological data were extracted from the official website of the National Bureau of Statistics. Global Moran's I, local Getis-Ord G_i^⁎ hotspot statistics, and Kulldorff's retrospective space-time scan statistical analysis were used to detect the spatial and spatiotemporal clusters of scarlet fever across all settings. A spatial panel data model was conducted to estimate the impact of meteorological factors on scarlet fever incidence.

RESULTS

Scarlet fever in China had obvious spatial, temporal, and spatiotemporal clustering, high-incidence spatial clusters were located mainly in the north and northeast of China. Nine spatiotemporal clusters were identified. A spatial lag fixed effects panel data model was the best fit for regression analysis. After adjusting for spatial individual effects and spatial autocorrelation (ρ = 0.5623), scarlet fever incidence was positively associated with a one-month lag of average temperature, precipitation, and total sunshine hours (all P-values < 0.05). Each 10 °C, 2 cm, and 10 h increase in temperature, precipitation, and sunshine hours, respectively, was associated with a 6.41% increment and 1.04% and 1.41% decrement in scarlet fever incidence, respectively.

CONCLUSION

The incidence of scarlet fever in China showed an upward trend in recent years. It had obvious spatiotemporal clustering, with the high-risk areas mainly concentrated in the north and northeast of China. Areas with high temperature and with low precipitation and sunshine hours tended to have a higher scarlet fever incidence, and we should pay more attention to prevention and control in these places.

Epidemiological study of scarlet fever in Shenyang, China

Background

Since 2011, there has been an increase in the incidence of scarlet fever across China. The main objective of this study was to depict the spatiotemporal epidemiological characteristics of the incidence of scarlet fever in Shenyang, China, in 2018 so as to provide the scientific basis for effective strategies of scarlet control and prevention.

Methods

Excel 2010 was used to demonstrate the temporal distribution at the month level and ArcGIS10.3 was used to demonstrate the spatial distribution at the district/county level. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation and the Getis-Ord statistic was used to determine the hot-spot areas of scarlet fever.

Results

A total of 2314 scarlet fever cases were reported in Shenyang in 2018 with an annual incidence of 31.24 per 100,000. The incidence among males was higher than that among females(p<0.001). A vast majority of the cases (96.89%) were among children aged 3 to 11 years. The highest incidence was 625.34/100,000 in children aged 5–9 years. In 2018 there were two seasonal peaks of scarlet fever in June (summer-peak) and December (winter-peak). The incidence of scarlet fever in urban areas was significantly higher than that in rural areas(p<0.001). The incidence of scarlet fever was randomly distributed in Shenyang. There are hotspot areas located in seven districts.

Conclusions

Urban areas are the hot spots of scarlet fever and joint prevention and control measures between districts should be applied. Children aged 3–11 are the main source of scarlet fever and therefore the introduction of prevention and control into kindergarten and primary schools may be key to the control of scarlet fever epidemics.

Predominance of emm4 and antibiotic resistance of Streptococcus pyogenes in acute pharyngitis in a southern region of Korea

BACKGROUND

Streptococcus pyogenes is the most common cause of bacterial pharyngitis. Genotyping of emm is useful for molecular epidemiological survey of S. pyogenes. Antibiotic resistance data are needed for empirical treatments.

METHODS

In total, 358 children in Changwon, Korea who had pharyngitis symptoms were subjected to throat cultures to isolate S. pyogenes in 2017. emm genotyping was performed by direct sequencing. An antibiotic susceptibility test was performed using the disk diffusion method for erythromycin (ERY), clindamycin (CLI), tetracycline (TET) and ofloxacin (OFX). Screening for macrolide resistance phenotype and its determinants was performed for the ERY-resistant strains.

RESULTS

A total of 190 strains (53.1 %) of S. pyogenes were isolated from 358 children. The most frequent emm genotype was emm4 (53.2 %), followed by emm89 (12.6 %), emm28 (11.6 %) and emm1 (10 %). Antibiotic resistance rates to ERY, CLI, TET and OFX were 3.2 %, 2.6 %, 1.1 % and 2.6%, respectively. There were five isolates of the cMLSB phenotype having the ermB gene and one M phenotype harbouring the mefA gene.

CONCLUSIONS

The distribution of emm genotypes was quite different from those previously reported in Korea. emm4 accounted for more than 50  % of the genotypes. Macrolide resistance rates remained very low, but five of six ERY-resistant strains displayed the cMLSB phenotype.

Incidence of Scarlet Fever in Children in Jeju Province, Korea, 2002-2016: An Age-period-cohort Analysis

Objectives:

Outbreaks of scarlet fever in Mexico in 1999, Hong Kong and mainland China in 2011, and England in 2014-2016 have received global attention, and the number of notified cases in Korean children, including in Jeju Province, has also increased since 2010. To identify relevant hypotheses regarding this emerging outbreak, an age-period-cohort (APC) analysis of scarlet fever incidence was conducted among children in Jeju Province, Korea.

Methods:

This study analyzed data from the nationwide insurance claims database administered by the Korean National Health Insurance Service. The inclusion criteria were children aged ≤14 years residing in Jeju Province, Korea who received any form of healthcare for scarlet fever from 2002 to 2016. The age and year variables were categorized into 5 groups, respectively. After calculating the crude incidence rate (CIR) for age and calendar year groups, the intrinsic estimator (IE) method was applied to conduct the APC analysis.

Results:

In total, 2345 cases were identified from 2002 to 2016. Scarlet fever was most common in the 0-2 age group, and boys presented more cases than girls. Since the CIR decreased with age between 2002 and 2016, the age and period effect decreased in all observed years. The IE coefficients suggesting a cohort effect shifted from negative to positive in 2009.

Conclusions:

The results suggest that the recent outbreak of scarlet fever among children in Jeju Province might be explained through the cohort effect. As children born after 2009 showed a higher risk of scarlet fever, further descriptive epidemiological studies are needed.

Incidence and Characteristics of Scarlet Fever, South Korea, 2008-2015

The incidence rate for scarlet fever in South Korea is rising. During 2008–2015, we collected group A Streptococcus isolates and performed emm and exotoxin genotyping and disk-diffusion antimicrobial tests. Scarlet fever in South Korea was most closely associated with emm types emm4, emm28, emm1, and emm3. In 2015, tetracycline resistance started increasing.

Spatiotemporal epidemiology of scarlet fever in Jiangsu Province, China, 2005-2015

Background

A marked increase in the incidence rate of scarlet fever imposed a considerable burden on the health of children aged 5 to 15 years. The main purpose of this study was to depict the spatiotemporal epidemiological characteristics of scarlet fever in Jiangsu Province, China in order to develop and implement effective scientific prevention and control strategies.

Methods

Smoothed map was used to demonstrate the spatial distribution of scarlet fever in Jiangsu Province. In addition, a retrospective space-time analysis based on a discrete Poisson model was utilized to detect clusters of scarlet fever from 2005 to 2015.

Results

During the years 2005–2015, a total of 15,873 scarlet fever cases occurred in Jiangsu Province, with an average annual incidence rate of 1.87 per 100,000. A majority of the cases (83.67%) occurred in children aged 3 to 9 years. Each year, two seasonal incidence peaks were observed, the higher occurring between March and July, the lower between November and the following January. The incidence in the southern regions of the province was generally higher than that in the northern regions. Seven clusters, all of which occurred during incidence peaks, were detected via space-time scan statistical analysis. The most likely cluster and one of the secondary clusters were detected in the southern and northern high endemic regions, respectively.

Conclusion

The prevalence of scarlet fever in Jiangsu Province had a marked seasonality variation and was relatively endemic in some regions. Children aged 3 to 9 years were the major victims of this disease, and kindergartens and primary schools were the focus of surveillance and control. Targeted strategies and measures should be taken to reduce the incidence.